NRI-Small: Expert-Apprentice Collaboration

机器人平台的最新进展已经超过了我们有效地对机器人进行编程以完成有用任务的能力，通常是在它们与人类共享的复杂环境中。为了让灵活、通用的机器人变得广泛，例如在向儿童传授技能、帮助老年人方面，必须有一种超越编程的与它们互动的方式。演示教学为在广泛的应用中实现大规模个人机器人的前景提供了一种潜在的强大和实用的方法。在演示教学中，专家(人)在不同于学徒或学生(机器人)使用的硬件上演示任务。该项目旨在开发基于视觉特征的方法，允许机器人通过统一学徒学习、示范学习(或模仿)和教学人类来教授人类，同时考虑到专家和学徒之间的差异。最终的系统将在PR2机器人上进行评估(主要是在抓取和操纵任务上)。该项目在示范学习和模仿学习方面取得的科学进步，都是具有广泛适用性的一般技术，将大大简化机器人的编程，这将使非专家用户更容易执行这项目前需要相当多的机器人学和计算机科学专门知识的重要任务。这项研究的更广泛影响包括开发新的机器人课程，在计算机视觉、机器学习和机器人技术的交叉点增加基于研究的跨学科培训的机会，推广活动(包括参加公立学校机器人教学计划)。所有研究成果，包括出版物、开源软件和数据集，都将免费提供给更大的科学界和学术界。

Recent advances in robot platforms have outpaced our ability to effectively program robots to accomplish useful tasks, often in complex environments that they share with humans. In order for flexible, general purpose robots to become widespread e.g., in teaching skills to children, assisting the elderly, there must be a way of interacting with them beyond programming. Teaching by demonstration offers a potentially powerful and practical approach to realizing the promise of large scale personal robotics in a wide range of applications. In teaching by demonstration, the expert (human), demonstrates the task on different hardware than what the apprentice or student (robot) uses. The project aims to develop visual feature-based methods that allow robots to teach humans and learn from them by unifying apprenticeship learning, learning by demonstration (or by imitation) and teaching humans, taking into account the differences between experts and apprentices. The resulting system will be evaluated on a PR2 robot (mostly on grasping and manipulation tasks). The scientific advances resulting from the project in learning from demonstration and imitation learning, both general techniques with broad applicability, will greatly simplify the programming of robots which would make it easier for non-expert users to perform this important task which currently requires considerable expertise in robotics as well as computer science. Broader impacts of the research include development of new robotics curricula, enhanced opportunities for research-based interdisciplinary training at the intersection of computer vision, machine learning, and robotics, outreach activities (including participation in a public school robotics instruction program). All of the results of the research, including publications, open-source software and datasets, will be made freely available to the larger scientific and academic community.